Abstract

Objective / Purpose: Online social relationships through the emergence of Web 2.0 applications have become a new trend for researchers to study the behavior of consumers to shop online, as well as social networking sites are technologies that opened up opportunities for new business models. Therefore, a new trend has emerged, called social trade technology. In order to understand the behavioral intentions of the beneficiaries to adopt the technology of social trade, the current research aims at developing an electronic readiness framework and UTAUT model to understand the beneficiary's adoption of social trade technology.

Design/ methodology/ Approach: To achieve the obje

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

   This paper proposed to build an authentication system between business partners on e-commerce application to prevent the frauds operations based on visual cryptography shares encapsulated by chen’s hyperchaotic key sequence. The proposed system consist of three phases, the first phase based on the color visual cryptography without complex computations, the second phase included generate sequence of DNA rules numbers and finally encapsulation phase is implemented based on use the unique initial value that generate in second phase as initial condition with Piecewise Linear Chaotic Maps to generate sequences of DNA rules numbers. The experimental results demonstrate the proposed able to overcome on cheating a

    With the explosive growth of data, it has become very difficult for a person to process the data and find the right information from it. So, to discover the right information from the colossal amount of data that is available online, we need information filtering systems. Recommendation systems (RS) help users find the most interesting information among the options that are available. Ratings given by the users play a vital role in determining the purposes of recommendations. Earlier, researchers used a user’s rating history to predict unknown ratings, but recently a user’s review has gained a lot of attention as it contains a lot of relevant information about a user’s decision. The proposed system makes an attempt to deal w

   E-commerce is the most important result of information technology in this day and age, has resulted in the use of commercial transactions to changes in economic, social, and psychological, and produced a new type of shopping, jobs, and create new job opportunities, and changed the traditional work environment. The challenge currently facing economic units is how to transfer this technology and its integration within the community, especially after the massive developments that have occurred in the areas of commercial and congested markets units, the economic and the products and services the many and varied and intensified competition among these units to achieve a profit, leading to the emergence of e-commerce as on

This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

The use of online social network (OSN) has become essential to humans' lives whether for entertainment, business or shopping. This increasing use of OSN motivates designing and implementing special systems that use OSN users' data to provide better user experience using machine learning and data mining algorithms and techniques. One system that is used extensively for this purpose is friend recommendation system (FRS) in which it recommends users to other users in professional or entertaining online social networks.

For this purpose, this study proposes a novel friend recommendation system, namely Hybrid Friend Recommendation (FR) model. The Hybrid model applies dual-stage methodology on unlabeled data of 1241 users collected fro

The e-commerce is one of the best achievements of the twentieth century, since the conduct commercial transactions via the Internet may be the consumer easy selection process and purchase convenient manner different from traditional methods, and with the beginnings of the new millennium impose the emergence of e-commerce term significant challenges to the insurance industry as an important economic sectors Generally, and insurance companies in particular as a result of scientific development, which has led to a reduction in costs and innovation in the production, which led to intense competition on both levels local or global. The insurance industry is a vital part of the economy and it has a varied impact to the community and individual

One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,